Application of Near Infrared Spectroscopy Technique Based on Support Vector Machine in the Measurement of Moisture and Protein Contents in Surimi
WANG Xiao-yan, WANG Xi-chang*, LIU Yuan*, DONG Ruo-yan
College of Food Science and Technology, Shanghai Engineering Research Center of Aquatic-Product Processing & Preservation, Shanghai Ocean University, Shanghai 201306, China
Abstract：Near infrared spectroscopy calibration models for moisture and protein contents of surimi were established by support vector machine (SVM), and predicted by independent sample set. The spectra processed by first derivative gap two (DB1G2), standard normal variation (SNV) and multiplicative scatter correction (MSC), then compressed by partial least squares (PLS), and the first fifteen were taken as variables. The correlation coefficient of calibration (Rc), correlation coefficient of validation (Rv), standard error of calibration (SEC) and standard error of prediction(SEP) of moisture model were 0.97, 0.95, 0.53 and 0.58, respectively. The Rc, Rv, SEC and SEP of protein model were 0.99, 0.98, 0.36 and 0.39, respectively. The two models had good recurrence. Therefore, NIR spectroscopy based on SVR can be applied to rapidly predict moisture and protein contents in surimi.
王小燕，王锡昌*，刘 源*，董若琰. 基于SVM算法的近红外光谱技术在鱼糜水分和蛋白质检测中的应用[J]. 光谱学与光谱分析, 2012, 32(09): 2418-2421.
WANG Xiao-yan, WANG Xi-chang*, LIU Yuan*, DONG Ruo-yan. Application of Near Infrared Spectroscopy Technique Based on Support Vector Machine in the Measurement of Moisture and Protein Contents in Surimi . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32(09): 2418-2421.
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